Model of Search and Analysis of Heterogeneous User Data to Improve the Web Projects Functioning

Autor: Anna Shilinh, Oleg Mastykash, Yuriy Syerov, Solomiia Fedushko
Rok vydání: 2021
Předmět:
Zdroj: Advances in Computer Science for Engineering and Education IV ISBN: 9783030804718
Popis: This study deal with the actual problem for modern science, which is associated with the management of web services, namely the operation management of web projects. The authors developed a model for searching and analyzing heterogeneous user data to improve the functioning of web projects. Means of detection and analysis of heterogeneous data in web project environments are modeled in the work. In this article was analyzed the content of a number of web-project platforms. The authors have developed a general algorithm for searching data in a web project environment and an algorithm for searching heterogeneous data. The collected data from various sources was filtered and consolidated into a single information resource, access to which is provided by the developed data search systems. The proposed methods have improved and simplified the processes of monitoring company employees. Practical implementation has been carried out on popular web projects on Facebook, Instagram, Youtube, TikTok, Pinterest, and LinkedIn.
Databáze: OpenAIRE